Coral holobiont physiology under ocean acidification and warming
Last run on 28 April 2021
Principal component analyses
Methods:
Principal component analysis (PCA) (function prcomp) of scaled and centered physiological parameters (host carbohydrate, host lipid, host protein, algal endosymbiont chlorophyll a, algal endosymbiont cell density, holobiont calcification rate as previously for the same samples in Bove et al. (2019)) were employed to assess the relationship between physiological parameters and treatment conditions for each coral species. Main effects (temperature, pCO2, and reef environment) were evaluated with PERMANOVA using the adonis2 function (vegan package; version 2.5.7).
Results:
Two principal components (PCs) explained approximately 66% of the variance in physiological responses of the S. siderea holobiont to ocean acidification and warming treatments (Figure 1A). PC1 was driven by differences in algal endosymbiont physiology (chlorophyll a, cell density), while PC2 represented an inverse relationship between host energy reserves (lipid, protein, carbohydrate) and calcification rates and colour intensities. Overall, lower pCO2 and temperature resulted in higher S. siderea holobiont physiology (Figure 1A). Treatment pCO2 predominantly drove S. siderea physiological responses (p < 0.001; Table S2), while temperature and reef environment were not as strong of drivers in physiological responses (p > 0.01 and p > 0.01, respectively; Table S2). For P. strigosa, 74% of the variance in the holobiont responses to treatments was explained by two PCs (Figure 1B). PC1 explained most of the variation of physiological parameters with the exception of host lipid content, which was represented in PC2. Holobiont physiology of P. strigosa was clearly reduced under warming and was generally higher in the lower pCO2 treatments (Figure 1B). Treatment temperature (p < 0.001; Table S2), pCO2 (p < 0.01; Table S2), and natal reef environment all significantly drove coral holobiont physiology (p < 0.001; Table S2). Finally, the first two PCs explained about 59% of the total variance of the P. astreoides holobiont response to treatment (Figure 1C). Coral holobiont samples separated most clearly along PC1 driven primarily by calcification rate and algal endosymbiont density, while PC2 exhibited an inverse relationship between host total carbohydrate and colour intensity. Overall, lower pCO2 drove higher P. astreoides holobiont physiology, while elevated temperature resulted in greater holobiont physiology (Figure 1C). Temperature (p < 0.001; Table S2) and pCO2 (p < 0.001; Table S2) drove separations in P. astreoides holobiont physiology, while reef environment was nonsignificant (p = 0.82; Table S2).
Siderastrea siderea
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = sid_pca_df ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 150243 0.27232 11.4516 0.0006662 ***
## ftemp 1 24935 0.04520 5.7018 0.0053298 **
## reef 1 26681 0.04836 6.1009 0.0033311 **
## Residual 80 349861 0.63413
## Total 85 551720 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Pseudodiploria strigosa
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = dip_pca_df ~ reef + fpco2 + ftemp, data = p_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## reef 1 162037 0.07959 10.9355 0.0006662 ***
## fpco2 3 196323 0.09644 4.4165 0.0019987 **
## ftemp 1 625389 0.30720 42.2061 0.0006662 ***
## Residual 71 1052041 0.51677
## Total 76 2035789 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Porites astreoides
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = por_pca_df ~ reef + ftemp + fpco2, data = a_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## reef 1 505 0.00150 0.1692 0.8194537
## ftemp 1 56228 0.16639 18.8252 0.0006662 ***
## fpco2 3 96015 0.28412 10.7153 0.0006662 ***
## Residual 62 185186 0.54799
## Total 67 337935 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Figure 1
Figure 1. Principal component analysis (PCA) of all coral holobiont physiological parameters for S. siderea (A), P. strigosa (B), and P. astreoides (C) after 93 days of exposure to different temperature and pCO2 treatments. PCAs in the top row are depicted by temperature treatment for each species (28\(^\circ\) C blue; 31\(^\circ\) C red) and the bottom row of PCAs are depicted by pCO2 for each species (280 \(\mu\)atm light purple; 400 \(\mu\)atm dark purple; 700 \(\mu\)atm light orange; 2800 \(\mu\)atm dark orange). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Figure S1
Figure S1. Principal component analysis (PCA) of all coral holobiont physiological parameters for S. siderea (A), P. strigosa (B), and P. astreoides (C) depicted by natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Correlation assessments
Methods:
Correlations of all physiological parameters were assessed to determine the relationships between parameters within each species, redargless of temperature and pCO2 treatment. The Pearson correlation coefficient (R2) of each comparison was calculated using the corrgram package (version 1.13) and the significance was calculated using the cor.test function. These relationships were then visualized through simple scatterplots.
Results:
Correlations of coral holobiont physiological parameters were generally positively related with one another across all three species. Correlations between S. siderea holobiont physiological parameters identified 15 significant relationships out of all 21 possible comparisons (Figure 2A). Of those significant correlations, six resulted in a Pearson's correlation coefficient (R2) equal to or greater than 0.5, with the strongest relationship identified being symbiont density vs chlorophyll a (R2 = 0.72). All pairwise physiological parameters were significantly correlated with one another in P. strigosa and of those, 14 correlations exhibit moderate (R2 > 0.50) positive relationships (Figure 2B). Notably, the two strongest correlations were host carbohydrate vs host protein (R2 = 0.70) and host carbohydrate vs chlorophyll a (R2 = 0.76). Compared to both S. siderea and P. strigosa, fewer physiological traits were significantly (p < 0.05) correlated with one another in P. astreoides (12 significant out of 21 total comparisons; Figure 2C). Of the significant correlations, only two pairwise comparisons resulted in a Pearson's correlation coefficient greater than 0.5: chlorophyll a vs colour intensity (R2 = 0.57) and host carbohydrate vs host protein (R2 = 0.68).
Figure 2. Coral holobiont correlation matrices (bottom panel) and scatter plots (top panel) for S. siderea (A), P. strigosa (B), and P. astreoides (C) depicting pairwise comparisons of physiological parameters within each species. Strength of correlations between parameters is indicated by darker shades of blue in the bottom panel with a higher R2 value (Pearson correlation coefficient). Of these correlations, significant correlations are depicted with asterisks according to significance level (* p < 0.05; ** p < 0.01; *** p < 0.001). Scatter plots of physiological parameters are displayed in the top panel with temperature depicted by shape (28\(^\circ\)C filled points; 31\(^\circ\)C open points) and pCO2 depicted by colour (280 \(\mu\)atm light purple; 400 \(\mu\)atm dark purple; 700 \(\mu\)atm light orange; 2800 \(\mu\)atm dark orange).
Plasticity analyses
Methods:
Using PC1 and PC2 for each species, we then calculated the phenotypic plasticity of each experimental fragment. Plasticity was calculated as the PC distance between an experimental fragment and the control (400 \(\mu\)atm; 28\(^\circ\)C) fragment from that same colony. The effects of treatment (pCO2 and temperature) and natal reef environment on calculated distances were assessed using generalized linear models (function glm) with a Gamma distribution and log-link. The best-fit model was selected as the model with the lowest AIC for each species (Table S1). The main effects of treatment and reef environment were assessed with an ANOVA (package car; version 3.0.10) with a type III error.
Results:
Natal reef environment (p < 0.05) and pCO2 (p < 0.05) significantly altered the phenotypic plasticity of S. siderea (Figure 3A; Table S3, S4). Offshore fragments exhibited a positive linear trend with increasing pCO2 while the inshore fragments appear to respond in a parabolic pattern to pCO2, with the lowest calculated distances occurring at 400 \(\mu\)atm, 31\(^\circ\)C and 700 \(\mu\)atm, 28\(^\circ\)C. Plasticity of P. strigosa and P. astreoides was not significantly altered by temperature treatment, pCO2 treatment, or natal reef environment (Figure 3B, 3C; Table S3, S4). However, P. astreoides exhibited a slight trend in the inshore fragments suggesting potentially higher plasticity with increasing pCO2 that is not seen in the offshore fragments (Figure 3C).
Siderastrea siderea
##
## Call:
## glm(formula = dist ~ reef * fpco2 + ftemp, family = Gamma(link = "log"),
## data = sid_dist, contrasts = list(reef = contr.sum, fpco2 = contr.sum,
## ftemp = contr.sum))
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.5392 -0.4066 -0.1219 0.2076 1.6019
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.75433 0.08433 8.945 5.45e-13 ***
## reef1 -0.20433 0.08271 -2.470 0.0161 *
## fpco21 -0.11652 0.14635 -0.796 0.4288
## fpco22 -0.13498 0.18076 -0.747 0.4579
## fpco23 -0.12823 0.13205 -0.971 0.3351
## ftemp1 -0.02907 0.08563 -0.339 0.7353
## reef1:fpco21 0.30174 0.14331 2.106 0.0390 *
## reef1:fpco22 -0.24282 0.16729 -1.451 0.1514
## reef1:fpco23 -0.04294 0.13049 -0.329 0.7431
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for Gamma family taken to be 0.4613617)
##
## Null deviance: 36.807 on 74 degrees of freedom
## Residual deviance: 27.862 on 66 degrees of freedom
## AIC: 254.68
##
## Number of Fisher Scoring iterations: 6## Analysis of Deviance Table (Type III tests)
##
## Response: dist
## Error estimate based on Pearson residuals
##
## Sum Sq Df F values Pr(>F)
## reef 2.7883 1 6.0436 0.01659 *
## fpco2 4.3615 3 3.1512 0.03064 *
## ftemp 0.0514 1 0.1114 0.73965
## reef:fpco2 2.2148 3 1.6002 0.19774
## Residuals 30.4499 66
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Pseudodiploria strigosa
##
## Call:
## glm(formula = dist ~ reef + fpco2 + ftemp, family = Gamma(link = "log"),
## data = dip_dist, contrasts = list(reef = contr.sum, fpco2 = contr.sum,
## ftemp = contr.sum))
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.42095 -0.58130 -0.06819 0.29076 1.27882
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.84433 0.09178 9.199 1.93e-13 ***
## reef1 0.04349 0.07514 0.579 0.565
## fpco21 0.08559 0.12845 0.666 0.508
## fpco22 0.07124 0.23272 0.306 0.760
## fpco23 -0.11009 0.14111 -0.780 0.438
## ftemp1 -0.03461 0.08164 -0.424 0.673
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for Gamma family taken to be 0.3908735)
##
## Null deviance: 27.294 on 71 degrees of freedom
## Residual deviance: 26.566 on 66 degrees of freedom
## AIC: 242.16
##
## Number of Fisher Scoring iterations: 6## Analysis of Deviance Table (Type III tests)
##
## Response: dist
## Error estimate based on Pearson residuals
##
## Sum Sq Df F values Pr(>F)
## reef 0.1283 1 0.3283 0.5686
## fpco2 0.4785 3 0.4081 0.7477
## ftemp 0.0675 1 0.1727 0.6791
## Residuals 25.7977 66
Porites astreoides
##
## Call:
## glm(formula = dist ~ reef + fpco2 + ftemp, family = Gamma(link = "log"),
## data = por_dist, contrasts = list(reef = contr.sum, fpco2 = contr.sum,
## ftemp = contr.sum))
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.3919 -0.4125 -0.0464 0.2664 1.1198
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.86006 0.07731 11.125 3.01e-15 ***
## reef1 -0.01244 0.07151 -0.174 0.8626
## fpco21 -0.04309 0.12083 -0.357 0.7228
## fpco22 -0.20977 0.18520 -1.133 0.2627
## fpco23 0.08610 0.11634 0.740 0.4626
## ftemp1 -0.15115 0.07883 -1.917 0.0608 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for Gamma family taken to be 0.2725499)
##
## Null deviance: 16.944 on 56 degrees of freedom
## Residual deviance: 15.563 on 51 degrees of freedom
## AIC: 188.39
##
## Number of Fisher Scoring iterations: 5## Analysis of Deviance Table (Type III tests)
##
## Response: dist
## Error estimate based on Pearson residuals
##
## Sum Sq Df F values Pr(>F)
## reef 0.0082 1 0.0300 0.86317
## fpco2 0.6725 3 0.8225 0.48753
## ftemp 1.0393 1 3.8133 0.05635 .
## Residuals 13.9000 51
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Figure 3
Figure 3. Assessment of phenotypic plasticity of S. siderea (A), P. strigosa (B), and P. astreoides (C) in experimental treatments and by natal reef environment. Higher values represent greater plasticity in coral holobiont samples. pCO2 treatment is depicted by colour and shape (280 \(\mu\)atm light purple, circle; 400 \(\mu\)atm dark purple, diamond; 700 \(\mu\)atm light orange, triangle; 2800 \(\mu\)atm dark orange, square) and temperature is represented as either filled (28\(^\circ\)C) or open (31\(^\circ\)C) symbols.
Siderastrea siderea subset
Methods:
Using the subset of S. siderea fragments with known Symbiodinacaea community composition identified from transcriptomic analyses (described below), we further assessed the differences in coral holobiont physiological responses by dominant symbiont genera. Relative abundance of Symbiodinacaea genus within each fragment was assigned as either Cladocopium spp. dominated (> 50% reads mapping to Cladocopium) or Durusdinium spp. dominated (> 50% reads mapping to Durusdinium). A PCA was performed with all coral holobiont physiological parameters with the addition of percent of reads mapping to Cladocopium spp. such that higher percentages represented Cladocopium dominated fragments and lower percentages represented Durusdinium dominated fragments. The phenotypic plasticity of the subset of S. siderea fragments was also assessed using the same methods described above. The effects of dominant Symbiodinacaea genus and treatment (pCO2 and temperature) were assessed using a generalized linear models (function glm) with a Gamma distribution and log-link and main effects were assessed with an ANOVA (package car; version 3.0.10) with a type III error. All figures and statistical analyses were carried out in R version 3.6.3 (R Core Development Team 2016).
Results:
Two principal components (PCs) explained approximately 60% of the variance in holobiont physiological responses of the subset of S. siderea fragments (Figure 4A). Interestingly, PC2 was driven by differences in Symbiodinacaea genera, along with host lipid content and colour intensity, while PC1 represented host carbohydrate and symbiont cell density. Fragments of S. siderea hosting higher abundances of Cladocopium spp. symbionts exhibited faster calcification rates while fragments dominated by Durusdinium spp. tended to have higher host lipid and protein content (Figure 4A). Experimental pCO2 (p < 0.001) and temperature (p < 0.01), dominant Symbiodinacaea genus (p < 0.001), and natal reef environment (p < 0.01) all significantly altered the holobiont physiology in the subset of S. siderea (Figure S2; Table S5). Analysis of the subset of S. siderea holobiont fragments suggests that dominant Symbiodinacaea genus (p = 0.05) and pCO2 (p = 0.05) altered the phenotypic plasticity in these samples (Figure 4B; Table S6, S7), however, the small sample size and marginal p value should be noted with interpretation.
Principal component analysis
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = sid_sub_pca_df ~ fpco2 + ftemp + reef + domSymb, data = s_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 60040 0.26137 7.9918 0.0006662 ***
## ftemp 1 13659 0.05946 5.4543 0.0046636 **
## reef 1 18472 0.08041 7.3763 0.0019987 **
## domSymb 1 44886 0.19540 17.9243 0.0006662 ***
## Residual 37 92656 0.40336
## Total 43 229711 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation assessments
Not sure I want to include this? But maybe put it in the supplemental materials!
Siderastrea siderea subset correlations
Siderastrea siderea dominated by Cladocopium spp. correlations
Siderastrea siderea dominated by Durusdinium spp. correlations
Plasticity analysis
##
## Call:
## glm(formula = dist ~ fpco2 + ftemp + domSymb, family = Gamma(link = "log"),
## data = sid_sub_dist, contrasts = list(domSymb = contr.sum,
## fpco2 = contr.sum, ftemp = contr.sum))
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.7027 -0.4627 -0.1325 0.3716 0.9130
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.81525 0.10753 7.582 8.3e-09 ***
## fpco21 -0.21184 0.16243 -1.304 0.2009
## fpco22 0.27727 0.20712 1.339 0.1896
## fpco23 -0.33164 0.14792 -2.242 0.0316 *
## ftemp1 0.03441 0.10175 0.338 0.7373
## domSymb1 -0.21391 0.10542 -2.029 0.0503 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for Gamma family taken to be 0.3249194)
##
## Null deviance: 19.816 on 39 degrees of freedom
## Residual deviance: 14.891 on 34 degrees of freedom
## AIC: 129.28
##
## Number of Fisher Scoring iterations: 7## Analysis of Deviance Table (Type III tests)
##
## Response: dist
## Error estimate based on Pearson residuals
##
## Sum Sq Df F values Pr(>F)
## fpco2 2.8270 3 2.9002 0.04905 *
## ftemp 0.0371 1 0.1142 0.73744
## domSymb 1.4188 1 4.3667 0.04420 *
## Residuals 11.0473 34
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Figure 4
Figure 4. Siderastrea siderea coral holobiont physiology based on dominant Symbiodinacaea genus. (A) Principal component analysis of all physiological parameters depicted by dominant Symbiodinacaea genus (Cladocopium spp. grey; Durusdinium spp. pink). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions. (B) Assessment of phenotypic plasticity based on dominant Symbiodinacaea genus with higher values represent greater plasticity in coral holobiont samples. pCO2 treatment is depicted by colour and shape (280 \(\mu\)atm light purple, circle; 400 \(\mu\)atm dark purple, diamond; 700 \(\mu\)atm light orange, triangle; 2800 \(\mu\)atm dark orange, square).
Figure S2
Figure S2. Principal component analysis of Siderastrea siderea coral holobiont physiology subset with known Symbiodinacaea community composition depicted by (A) pCO2 (280 \(\mu\)atm light purple; 400 \(\mu\)atm dark purple; 700 \(\mu\)atm light orange; 2800 \(\mu\)atm dark orange), (B) temperature treatment (28\(^\circ\) C blue; 31\(^\circ\) C red), and (C) natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Supplemental Tables
Table S1 WORKING
Figure S1. Akaike information criterion (AIC) generalized linear model (GLM) selection comparisons for plasticity assessments to select the best-fit model per species.| Name | AIC | BIC | R2_Nagelkerke | RMSE | Sigma | Performance_Score | species |
|---|---|---|---|---|---|---|---|
| Siderastrea Siderea | |||||||
| ssid_dist_mod2 | 254.6834 | 277.8583 | 0.2898819 | 1.292625 | 0.6497296 | 0.8547458 | SSID |
| ssid_dist_mod5 | 256.4133 | 281.9056 | 0.2927614 | 1.289972 | 0.6535980 | 0.7433569 | SSID |
| ssid_dist_mod4 | 254.7841 | 271.0065 | 0.2212939 | 1.336852 | 0.6602212 | 0.7188565 | SSID |
| ssid_dist_mod3 | 256.4597 | 277.3171 | 0.2482516 | 1.327032 | 0.6603239 | 0.6467928 | SSID |
| ssid_dist_mod | 260.3504 | 295.1127 | 0.3345573 | 1.259156 | 0.6576562 | 0.5526813 | SSID |
| ssid_dist_mod6 | 259.4286 | 273.3335 | 0.1381497 | 1.415132 | 0.6832328 | 0.2132253 | SSID |
| Pseudodiploria strigosa | |||||||
| pstr_dist_mod | 242.5167 | 276.6667 | 0.2401446 | 1.203140 | 0.6105555 | 0.6862242 | PSTR |
| pstr_dist_mod3 | 239.6818 | 260.1718 | 0.1248663 | 1.309967 | 0.6174577 | 0.6605645 | PSTR |
| pstr_dist_mod6 | 240.5284 | 254.1884 | 0.0263120 | 1.379562 | 0.6312036 | 0.3946846 | PSTR |
| pstr_dist_mod5 | 244.1928 | 269.2362 | 0.1179006 | 1.296067 | 0.6294493 | 0.3086050 | PSTR |
| pstr_dist_mod4 | 242.1604 | 258.0970 | 0.0319087 | 1.375956 | 0.6344371 | 0.2769026 | PSTR |
| pstr_dist_mod2 | 244.6651 | 267.4318 | 0.0833341 | 1.346315 | 0.6346577 | 0.1731917 | PSTR |
| Porites astreoides | |||||||
| past_dist_mod2 | 193.3184 | 213.7489 | 0.1115845 | 1.163774 | 0.5642888 | 0.6218453 | PAST |
| past_dist_mod6 | 186.4250 | 198.6833 | 0.0925414 | 1.176322 | 0.5472114 | 0.6002528 | PAST |
| past_dist_mod5 | 195.3178 | 217.7914 | 0.1115948 | 1.163725 | 0.5702574 | 0.5393449 | PAST |
| past_dist_mod4 | 188.3937 | 202.6950 | 0.0930860 | 1.176344 | 0.5524051 | 0.5256776 | PAST |
| past_dist_mod3 | 192.0251 | 210.4126 | 0.0994731 | 1.170654 | 0.5618251 | 0.4964299 | PAST |
| past_dist_mod | 200.9745 | 229.5772 | 0.1174163 | 1.159056 | 0.5876799 | 0.4000000 | PAST |
Table S2
Table S2. PERMANOVA model output from each species using the adonis2 function with 1500 iterations.| Df | Sum of Squares | R2 | F | P-value | |
|---|---|---|---|---|---|
| Siderastrea Siderea | |||||
| pCO2 | 3 | 150243 | 0.272 | 11.45 | 0.00067 |
| temperature | 1 | 24935 | 0.045 | 5.70 | 0.00533 |
| reef environment | 1 | 26681 | 0.048 | 6.10 | 0.00333 |
| Residual | 80 | 349861 | 0.634 | ||
| Total | 85 | 551720 | 1.000 | ||
| Pseudodiploria strigosa | |||||
| reef environment | 1 | 162037 | 0.080 | 10.94 | 0.00067 |
| pCO2 | 3 | 196323 | 0.096 | 4.42 | 0.00200 |
| temperature | 1 | 625389 | 0.307 | 42.21 | 0.00067 |
| Residual | 71 | 1052041 | 0.517 | ||
| Total | 76 | 2035789 | 1.000 | ||
| Porites astreoides | |||||
| reef environment | 1 | 505 | 0.001 | 0.17 | 0.81945 |
| temperature | 1 | 56228 | 0.166 | 18.83 | 0.00067 |
| pCO2 | 3 | 96015 | 0.284 | 10.72 | 0.00067 |
| Residual | 62 | 185186 | 0.548 | ||
| Total | 67 | 337935 | 1.000 | ||
Table S3
Table S3. GLM output from plasticity assessments for each species. The intercept of each model was set as 300 \(\mu\)atm, 28\(^\circ\)C, and inshore reef environment.| Estimate | Standard error | Statistic | P-value | |
|---|---|---|---|---|
| Siderastrea Siderea | ||||
| (Intercept) | 0.754 | 0.084 | 8.94 | 0.000 |
| reef environment (offshore) | -0.204 | 0.083 | -2.47 | 0.016 |
| pCO2-current | -0.117 | 0.146 | -0.80 | 0.429 |
| pCO2-EOC | -0.135 | 0.181 | -0.75 | 0.458 |
| pCO2 | -0.128 | 0.132 | -0.97 | 0.335 |
| temperature (31C) | -0.029 | 0.086 | -0.34 | 0.735 |
| reef environment (offshore):pCO2-current | 0.302 | 0.143 | 2.11 | 0.039 |
| reef environment (offshore):pCO2-EOC | -0.243 | 0.167 | -1.45 | 0.151 |
| reef environment (offshore):pCO2 | -0.043 | 0.130 | -0.33 | 0.743 |
| Pseudodiploria strigosa | ||||
| (Intercept) | 0.844 | 0.092 | 9.20 | 0.000 |
| reef environment (offshore) | 0.043 | 0.075 | 0.58 | 0.565 |
| pCO2-current | 0.086 | 0.128 | 0.67 | 0.508 |
| pCO2-EOC | 0.071 | 0.233 | 0.31 | 0.760 |
| pCO2 | -0.110 | 0.141 | -0.78 | 0.438 |
| temperature (31C) | -0.035 | 0.082 | -0.42 | 0.673 |
| Porites astreoides | ||||
| (Intercept) | 0.860 | 0.077 | 11.12 | 0.000 |
| reef environment (offshore) | -0.012 | 0.072 | -0.17 | 0.863 |
| pCO2-current | -0.043 | 0.121 | -0.36 | 0.723 |
| pCO2-EOC | -0.210 | 0.185 | -1.13 | 0.263 |
| pCO2 | 0.086 | 0.116 | 0.74 | 0.463 |
| temperature (31C) | -0.151 | 0.079 | -1.92 | 0.061 |
Table S4
Table S4. Type III test of analysis of deviance output based on the plasticity GLM per species in Table S3.| Sum of Squares | Df | F values | P-value | |
|---|---|---|---|---|
| Siderastrea Siderea | ||||
| reef environment | 2.79 | 1 | 6.0 | 0.02 |
| pCO2 | 4.36 | 3 | 3.2 | 0.03 |
| temperature | 0.05 | 1 | 0.1 | 0.74 |
| reef environment:pCO2 | 2.21 | 3 | 1.6 | 0.20 |
| Residuals | 30.45 | 66 | ||
| Pseudodiploria strigosa | ||||
| reef environment | 0.13 | 1 | 0.3 | 0.57 |
| pCO2 | 0.48 | 3 | 0.4 | 0.75 |
| temperature | 0.07 | 1 | 0.2 | 0.68 |
| Residuals | 25.80 | 66 | ||
| Porites astreoides | ||||
| reef environment | 0.01 | 1 | 0.0 | 0.86 |
| pCO2 | 0.67 | 3 | 0.8 | 0.49 |
| temperature | 1.04 | 1 | 3.8 | 0.06 |
| Residuals | 13.90 | 51 | ||
Table S5
Table S5. PERMANOVA model output from the Siderastrea siderea samples with known Symbiodiniaceae community composition using the adonis2 function with 1500 iterations.| Df | Sum of Squares | R2 | F | P-value | |
|---|---|---|---|---|---|
| pCO2 | 3 | 60040 | 0.261 | 7.99 | 0.00067 |
| temperature | 1 | 13659 | 0.059 | 5.45 | 0.00466 |
| reef environment | 1 | 18472 | 0.080 | 7.38 | 0.00200 |
| dominant symbiont | 1 | 44886 | 0.195 | 17.92 | 0.00067 |
| Residual | 37 | 92656 | 0.403 | ||
| Total | 43 | 229711 | 1.000 |
Table S6
Table S6. GLM output from plasticity assessments for the Siderastrea siderea samples with known Symbiodiniaceae community composition. The intercept of each model was set as 300 \(\mu\)atm, 28\(^\circ\)C, and Cladocopium spp. community dominance.| Estimate | Standard error | Statistic | P-value | |
|---|---|---|---|---|
| (Intercept) | 0.815 | 0.108 | 7.58 | 0.000 |
| pCO2-current | -0.212 | 0.162 | -1.30 | 0.201 |
| pCO2-EOC | 0.277 | 0.207 | 1.34 | 0.190 |
| pCO2 | -0.332 | 0.148 | -2.24 | 0.032 |
| temperature (31C) | 0.034 | 0.102 | 0.34 | 0.737 |
| dominant symbiont (D) | -0.214 | 0.105 | -2.03 | 0.050 |
Table S7
Table S7. Type III test of analysis of deviance output based on the plasticity GLM for the Siderastrea siderea samples with known Symbiodiniaceae community composition in Table S6.| Sum of Squares | Df | F values | P-value | |
|---|---|---|---|---|
| pCO2 | 2.83 | 3 | 2.9 | 0.05 |
| temperature | 0.04 | 1 | 0.1 | 0.74 |
| dominant symbiont | 1.42 | 1 | 4.4 | 0.04 |
| Residuals | 11.05 | 34 |
Session information
Session information from the last run date on 2021-04-28:
## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS High Sierra 10.13.6
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] grid stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] car_3.0-10 carData_3.0-4 png_0.1-7 MASS_7.3-53.1
## [5] performance_0.7.1 wesanderson_0.3.6 RColorBrewer_1.1-2 gridGraphics_0.5-1
## [9] corrplot_0.84 Hmisc_4.5-0 Formula_1.2-4 survival_3.2-10
## [13] magick_2.7.1 ggpubr_0.4.0 vroom_1.4.0 lmerTest_3.1-3
## [17] lme4_1.1-26 Matrix_1.3-2 kableExtra_1.3.4 finalfit_1.0.2
## [21] ggfortify_0.4.11 cowplot_1.1.1 Rmisc_1.5 shiny_1.6.0
## [25] vegan_2.5-7 lattice_0.20-41 permute_0.9-5 forcats_0.5.1
## [29] stringr_1.4.0 purrr_0.3.4 tibble_3.1.0 tidyverse_1.3.0
## [33] plotly_4.9.3 openxlsx_4.2.3 corrgram_1.13 tidyr_1.1.3
## [37] ggbiplot_0.55 scales_1.1.1 plyr_1.8.6 dplyr_1.0.5
## [41] ggplot2_3.3.3 broom_0.7.6 readr_1.4.0 knitr_1.31
##
## loaded via a namespace (and not attached):
## [1] readxl_1.3.1 backports_1.2.1 systemfonts_1.0.1
## [4] lazyeval_0.2.2 splines_3.6.3 digest_0.6.27
## [7] foreach_1.5.1 htmltools_0.5.1.1 fansi_0.4.2
## [10] checkmate_2.0.0 magrittr_2.0.1 cluster_2.1.1
## [13] see_0.6.3 modelr_0.1.8 svglite_2.0.0
## [16] jpeg_0.1-8.1 colorspace_2.0-0 ggrepel_0.9.1
## [19] rvest_1.0.0 haven_2.3.1 xfun_0.22
## [22] crayon_1.4.1 jsonlite_1.7.2 iterators_1.0.13
## [25] glue_1.4.2 registry_0.5-1 gtable_0.3.0
## [28] emmeans_1.5.5-1 webshot_0.5.2 abind_1.4-5
## [31] mvtnorm_1.1-1 DBI_1.1.1 rstatix_0.7.0
## [34] Rcpp_1.0.6 htmlTable_2.1.0 viridisLite_0.3.0
## [37] xtable_1.8-4 foreign_0.8-75 bit_4.0.4
## [40] htmlwidgets_1.5.3 httr_1.4.2 ellipsis_0.3.1
## [43] mice_3.13.0 farver_2.1.0 pkgconfig_2.0.3
## [46] nnet_7.3-15 sass_0.3.1 dbplyr_2.1.1
## [49] utf8_1.2.1 effectsize_0.4.4-1 labeling_0.4.2
## [52] tidyselect_1.1.0 rlang_0.4.10 later_1.1.0.1
## [55] munsell_0.5.0 cellranger_1.1.0 tools_3.6.3
## [58] cli_2.4.0 generics_0.1.0 ggridges_0.5.3
## [61] evaluate_0.14 fastmap_1.1.0 yaml_2.2.1
## [64] bit64_4.0.5 fs_1.5.0 zip_2.1.1
## [67] nlme_3.1-152 mime_0.10 xml2_1.3.2
## [70] compiler_3.6.3 rstudioapi_0.13 curl_4.3
## [73] ggsignif_0.6.1 reprex_2.0.0 statmod_1.4.35
## [76] bslib_0.2.4 stringi_1.5.3 parameters_0.13.0
## [79] highr_0.8 nloptr_1.2.2.2 vctrs_0.3.7
## [82] pillar_1.6.0 lifecycle_1.0.0 jquerylib_0.1.3
## [85] estimability_1.3 insight_0.13.2 data.table_1.14.0
## [88] seriation_1.2-9 httpuv_1.5.5 R6_2.5.0
## [91] latticeExtra_0.6-29 promises_1.2.0.1 TSP_1.1-10
## [94] gridExtra_2.3 rio_0.5.26 codetools_0.2-18
## [97] boot_1.3-27 assertthat_0.2.1 withr_2.4.1
## [100] bayestestR_0.9.0 mgcv_1.8-34 parallel_3.6.3
## [103] hms_1.0.0 rpart_4.1-15 coda_0.19-4
## [106] minqa_1.2.4 rmarkdown_2.7 numDeriv_2016.8-1.1
## [109] lubridate_1.7.10 base64enc_0.1-3